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Record W1561439374 · doi:10.1109/ihtc.2015.7238051

Exploring the citizen-driven response to crisis in cyberspace, risk and the need for resilience

2015· article· en· W1561439374 on OpenAlexaff
Jennie Phillips

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCyberspaceResilience (materials science)Context (archaeology)Psychological resiliencePolitical scienceDiasporaSociologyPublic relationsComputer scienceInternet privacyThe InternetGeographyPsychologySocial psychologyWorld Wide WebLaw

Abstract

fetched live from OpenAlex

This paper aims to contextualize the citizen-driven response to crisis in cyberspace, the risks they experience and the relationship with resilience. First, discussion will identify the four types of digital response networks (affected communities, diaspora, digital humanitarians and digital activists) and introduce Digital Humanitarian Activist Networks (DHANs). Second, Bronfennbrenners ecological systems theory is used to contextualize risk through three risk typologies: regional, network, and individual risk. Third, the suitability of organizational resilience is explained for this context, and the need to rethink existing theory is discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.197
Threshold uncertainty score0.565

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.076
GPT teacher head0.314
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2015
Admission routes1
Has abstractyes

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